abstract = "Information extraction (IE) is fundamental to numerous NLP applications, yet existing solutions often require specialized models for different tasks or rely on computationally expensive large language models. We present GLiNER2, a unified framework that enhances the original GLiNER architecture to support named entity recognition, text classification, and hierarchical structured data extraction within a single efficient model. Built on a fine-tuned encoder architecture, GLiNER2 maintains CPU efficiency and compact size while introducing multi-task composition through an intuitive schema-based interface. Our experiments demonstrate competitive performance across diverse IE tasks with substantial improvements in deployment accessibility compared to LLM-based alternatives. We release GLiNER2 as an open-source library available through pip, complete with pre-trained models and comprehensive documentation."
Пьяный турист нанес тяжелую травму участвовавшей в Олимпиаде сноубордистке20:38
。业内人士推荐爱思助手作为进阶阅读
——蔡强代表（海南省人民政府党组成员、秘书长）
The hosts must conjure the spirit of their last title triumph, 27 years ago, when the sides meet at Murrayfield
。业内人士推荐clash下载作为进阶阅读
В свою очередь, управляющий партнер хедж-фонда Amont Partners Роб Ли считает, что распродажи последних дней связаны с паникой инвесторов, а не с фундаментальными факторами, поэтому рынок продолжит рост.
США анонсировали крупнейшую бомбардировку Ирана01:55，更多细节参见heLLoword翻译官方下载